基于混合蛙跳算法的移动机器人路径规划

针对移动机器人路径规划中算法搜索能力不强且易陷入停滞的问题,文中提出了一种基于混合蛙跳算法的移动机器人路径规划方法。首先利用蚁群算法在栅格地图中生成一定数量的路径,然后引入混合蛙跳算法,子群内进行Memetic进化,最坏青蛙根据与子群最优青蛙或全局最优青蛙的路径交点栅格进行路径更新,并对最终生成的最优路径进行优化处理,以消除不必要的拐点,保证机器人路径运行的安全性。二维环境下的仿真实验表明,提出的混合蛙跳算法能在有效避开障碍物的同时快速地规划出一条通往目标点的优化路径,且效果令人满意。

Path Planning of Mobile Robot Based on Shuffled Frog Leaping Algorithm

To solve the problem of a method of path planning based on shuffled frog leaping algorithm is proposed to solve the poor search ability and stagnation in the mobile robot path planning.A certain number of paths are generated first in the grid map by the ant colony algorithm.Then,shuffled frog leaping algorithm is drawn in,and the worst frog updates its path according to the grids which intersect the paths of the best sub-group frogs or the global optimal frog.Finally,the generated path is optimized in order to eliminate unnecessary turning point and guarantee the moving safety of robot.Simulation under the two-dimension environment indicates that the proposed shuffled frog leaping algorithm can plan a safe and satisfactory optimal path quickly while avoiding obstacles effectively.